Final Report Summary - DEMOTEST-EV (DEsign, MOdelling and TESTing tools for Electrical Vehicles powertrain drives)
DeMoTest-EV project (http://www.demotest-ev.com/) brought together the competences and skills of four research teams from 2 universities and 2 companies for developing advanced and extended design, modelling and testing tools for improved concept modelling and for higher prediction accuracy of noise and vibration generated by EVs powertrain. The achievement of this objective was possible by enhancing knowledge, know-how and technological transfer between the four European partners bringing together their experience in electrical machines and drives, NVH issues in automotive, modelling and testing tools for automotive applications. The mechanisms used for the transfer of knowledge within the frame of the project were collaborative research, two-way intersectoral secondments, sharing facilities, training and dissemination activities.
In the frame of the project, as a result of the collaborative research, a design and modelling platform was developed, by connecting design and modelling modules developed under different open source and/or under licence software package in order to design and simulate three types of electrical machines and drives: permanent magnet, switched reluctance and synchronous reluctance. The models can be translated on testing test-benches providing the tools for testing and assessment of the machines under study.
DEMOTEST platform was developed as an advanced and extended design, modelling and testing tools for improved concept modelling and for higher prediction accuracy of noise and vibration generated by EVs powertrain. The platform offers the development and analysis of 3 types of motors: Surface Mounted Permanent Magnet Synchronous Motor (PMSM), Variable Reluctance Synchronous Motor (VRSM) and Switched Reluctance Motor (SRM). It can follow a flow chart or if can perform any task separately, by skipping any step presented.
At component-level, following the specifications (inputs and constraints), for the given machine type, a fast analytical design tool (in-house built and/or SPEED) is applied for comparing the different options and arriving at a first design. It will also be able to perform optimizations to minimize geometrical dimensions according to different objective functions (output power, efficiency, average torque, etc.) and to deliver sufficiently accurate models for system electromagnetic design task.
After the design of the machine, models are extracted for being implemented in the Electromagnetic design module, thus, either a numerical (using open source or licenced FE-based software packages) or analytical method (in-house built modules) is used for refining the magnetic design.
The mechanical behaviour of the machine is predicted assuming that the magnetic noise mainly comes from the Maxwell radial forces excitation of the mechanical structure composed of stator stack and frame. A 2D equivalent ring model, whose natural frequencies are computed analytically, will be used. The natural frequencies computation will be validated on the existing machines, using both FEA (JMAG Structural Analysis module) and experiments (Virtual.Lab).
The system-level module consists of two components: Model-in-the-Loop and Hardware-in-the-Loop modules. As part of a drive subsystem and further of the powertrain driveline, the electrical machine characteristics and performances should be evaluated at both subsystem and system level.
Therefore, at the drive level, for each machine under study, a mathematical model was developed, implemented and tested using the Matlab-Simulink environment. The subsystem-level model is able to connect with both electromagnetic FEA based model and with analytical electromagnetic-vibro-acoustic model. This way it provides both accurate and/or fast analysis of the converter and control strategy impact on the NVH performances of the machine.
For the evaluation of the electrical machine and its drive impact at powertrain level, a solution is provided describing the electromechanical component behaviour using, multi-dimensional look-up tables (as outputs of the electromagnetic model simulation). This model is imported into Imagine.Lab AMESim (available to LMS) as an electromechanical component and is easily connected with the driver circuit and to the load model. Using the built-in design capabilities of Lab.Amesim the off-line simulation MiL of different control strategies is possible. The models can be translated on testing test-benches providing the tools for testing and assessment of the machines under study.
During the project a total number of 19 researchers performed 99.5 PMs secondments: 9 ESR, 5 ER<10 and 5 ER>10. Three ER<10 were recruited, one by UTCN, one by ULB and one by SISW. They performed 43 PMs. Both the seconded and recruited researchers attended different training events organized inside and/or outside the consortium.
Thus, the project answered to one of the most important requirements of the automotive industry: enhancement of the effectiveness of research activities by industry-academia collaborative research. Therefore, the current project will impact positively upon the (i) involved researchers, (i) each partner as a whole and (III) on academia and automotive industry, as part of the results will be available for public dissemination.
The main achievement of the project is the high-level prepared researchers, both ESRs and ERs, capable to face the new challenges of the research and development activity in the complex and multidisciplinary field of automotive applications in general, and in traction driveline, in particular.
In the frame of the project, as a result of the collaborative research, a design and modelling platform was developed, by connecting design and modelling modules developed under different open source and/or under licence software package in order to design and simulate three types of electrical machines and drives: permanent magnet, switched reluctance and synchronous reluctance. The models can be translated on testing test-benches providing the tools for testing and assessment of the machines under study.
DEMOTEST platform was developed as an advanced and extended design, modelling and testing tools for improved concept modelling and for higher prediction accuracy of noise and vibration generated by EVs powertrain. The platform offers the development and analysis of 3 types of motors: Surface Mounted Permanent Magnet Synchronous Motor (PMSM), Variable Reluctance Synchronous Motor (VRSM) and Switched Reluctance Motor (SRM). It can follow a flow chart or if can perform any task separately, by skipping any step presented.
At component-level, following the specifications (inputs and constraints), for the given machine type, a fast analytical design tool (in-house built and/or SPEED) is applied for comparing the different options and arriving at a first design. It will also be able to perform optimizations to minimize geometrical dimensions according to different objective functions (output power, efficiency, average torque, etc.) and to deliver sufficiently accurate models for system electromagnetic design task.
After the design of the machine, models are extracted for being implemented in the Electromagnetic design module, thus, either a numerical (using open source or licenced FE-based software packages) or analytical method (in-house built modules) is used for refining the magnetic design.
The mechanical behaviour of the machine is predicted assuming that the magnetic noise mainly comes from the Maxwell radial forces excitation of the mechanical structure composed of stator stack and frame. A 2D equivalent ring model, whose natural frequencies are computed analytically, will be used. The natural frequencies computation will be validated on the existing machines, using both FEA (JMAG Structural Analysis module) and experiments (Virtual.Lab).
The system-level module consists of two components: Model-in-the-Loop and Hardware-in-the-Loop modules. As part of a drive subsystem and further of the powertrain driveline, the electrical machine characteristics and performances should be evaluated at both subsystem and system level.
Therefore, at the drive level, for each machine under study, a mathematical model was developed, implemented and tested using the Matlab-Simulink environment. The subsystem-level model is able to connect with both electromagnetic FEA based model and with analytical electromagnetic-vibro-acoustic model. This way it provides both accurate and/or fast analysis of the converter and control strategy impact on the NVH performances of the machine.
For the evaluation of the electrical machine and its drive impact at powertrain level, a solution is provided describing the electromechanical component behaviour using, multi-dimensional look-up tables (as outputs of the electromagnetic model simulation). This model is imported into Imagine.Lab AMESim (available to LMS) as an electromechanical component and is easily connected with the driver circuit and to the load model. Using the built-in design capabilities of Lab.Amesim the off-line simulation MiL of different control strategies is possible. The models can be translated on testing test-benches providing the tools for testing and assessment of the machines under study.
During the project a total number of 19 researchers performed 99.5 PMs secondments: 9 ESR, 5 ER<10 and 5 ER>10. Three ER<10 were recruited, one by UTCN, one by ULB and one by SISW. They performed 43 PMs. Both the seconded and recruited researchers attended different training events organized inside and/or outside the consortium.
Thus, the project answered to one of the most important requirements of the automotive industry: enhancement of the effectiveness of research activities by industry-academia collaborative research. Therefore, the current project will impact positively upon the (i) involved researchers, (i) each partner as a whole and (III) on academia and automotive industry, as part of the results will be available for public dissemination.
The main achievement of the project is the high-level prepared researchers, both ESRs and ERs, capable to face the new challenges of the research and development activity in the complex and multidisciplinary field of automotive applications in general, and in traction driveline, in particular.